Přístupnostní navigace
E-application
Search Search Close
Publication detail
ARORA, M DUTTA, M. K. TRAVIESO M. C. BURGET R.
Original Title
Image Processing Based Classification of Enzymatic Browning in Chopped Apples
Type
conference paper
Language
English
Original Abstract
Apples are one of the most common fruit on the planet. It is rich in iron, fiber, antioxidants and other nutritive quality; which are incredibly important for human body and brain. The quality of an apple gets affected once they are chopped. This paper presents a non-destructive image processing based algorithm that identifies the presence of enzymatic browning in chopped apples for the determination of its nutrients loss. The proposed imperative assemblage of this image processing algorithm makes it flexible, automatic and non-destructive. The quantification of enzymatic browning in chopped apples has been obtained with high precision using this proposed imaging based method. The machine learning based on strategic selection of discriminatory statistical features of chopped apples extracted in wavelet domain makes it a novel approach. 85% of accuracy has been achieved by using machine learning based Support Vector Machine (SVM) classifier.
Keywords
Image segmentation; Feature extraction; Image color analysis;Wavelet domain;Clustering algorithms;Cameras
Authors
ARORA, M; DUTTA, M. K.; TRAVIESO M. C.; BURGET R.
Released
18. 7. 2018
Publisher
2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)
Location
San Carlos, Costa Rica
ISBN
978-1-5386-7506-9
Book
Pages from
1
Pages to
8
Pages count
URL
https://ieeexplore.ieee.org/document/8464181
BibTex
@inproceedings{BUT150883, author="ARORA, M and DUTTA, M. K. and TRAVIESO M. C. and BURGET R.", title="Image Processing Based Classification of Enzymatic Browning in Chopped Apples", booktitle="2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)", year="2018", pages="1--8", publisher="2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)", address="San Carlos, Costa Rica", doi="10.1109/IWOBI.2018.8464181", isbn="978-1-5386-7506-9", url="https://ieeexplore.ieee.org/document/8464181" }